---
license: mit
tags:
- pytorch
- safetensors
- threshold-logic
- neuromorphic
---

# threshold-mux

2:1 multiplexer. Selects between two inputs based on a select signal.

## Circuit

```
    a   b   s
    │   │   │
    │   └───┼───┐
    └───┬───┘   │
        │   ┌───┘
        ▼   ▼
  ┌─────────────┐
  │  a AND ¬s   │   N1: w=[1,0,-1] b=-1
  └─────────────┘
        │
        │   ┌─────────────┐
        │   │  b AND s    │   N2: w=[0,1,1] b=-2
        │   └─────────────┘
        │         │
        └────┬────┘
             ▼
        ┌─────────┐
        │   OR    │   w=[1,1] b=-1
        └─────────┘
             │
             ▼
           output
```

## Function

MUX(a, b, s) = a if s=0, b if s=1

Equivalent to: OR(AND(a, NOT(s)), AND(b, s))

## Truth Table

| a | b | s | out |
|---|---|---|-----|
| 0 | 0 | 0 | 0 |
| 0 | 0 | 1 | 0 |
| 0 | 1 | 0 | 0 |
| 0 | 1 | 1 | 1 |
| 1 | 0 | 0 | 1 |
| 1 | 0 | 1 | 0 |
| 1 | 1 | 0 | 1 |
| 1 | 1 | 1 | 1 |

## Architecture

| Layer | Neurons | Weights | Bias |
|-------|---------|---------|------|
| 1 | N1 (a AND ¬s) | [1, 0, -1] | -1 |
| 1 | N2 (b AND s) | [0, 1, 1] | -2 |
| 2 | OR | [1, 1] | -1 |

**Total: 3 neurons, 11 parameters, 2 layers**

## Usage

```python
from safetensors.torch import load_file
import torch

w = load_file('model.safetensors')

def mux(a, b, s):
    inp = torch.tensor([float(a), float(b), float(s)])
    l1 = (inp @ w['layer1.weight'].T + w['layer1.bias'] >= 0).float()
    out = (l1 @ w['layer2.weight'].T + w['layer2.bias'] >= 0).float()
    return int(out.item())

print(mux(1, 0, 0))  # 1 (selects a)
print(mux(1, 0, 1))  # 0 (selects b)
```

## Files

```
threshold-mux/
├── model.safetensors
├── model.py
├── config.json
└── README.md
```

## License

MIT